Structural similarity comparison method

comparisons.py

@@ -1,6 +1,6 @@
 import cv2
 import numpy as np
-
+from skimage.metrics import structural_similarity
 
 def histogram_comparison(data_a: np.ndarray, data_b: np.ndarray) -> dict:
   hsv_a = cv2.cvtColor(data_a, cv2.COLOR_BGR2HSV)
@@ -23,3 +23,7 @@ def histogram_comparison(data_a: np.ndarray, data_b: np.ndarray) -> dict:
     'intersection': cv2.compareHist(hist_a, hist_b, 2),
     'bhattacharyya-distance': cv2.compareHist(hist_a, hist_b, 3),
   }
+
+
+def structural_similarity_index(data_a: np.ndarray, data_b: np.ndarray) -> float:
+  return structural_similarity(cv2.cvtColor(data_a, cv2.COLOR_BGR2GRAY), cv2.cvtColor(data_b, cv2.COLOR_BGR2GRAY))

main.py

@@ -3,7 +3,7 @@ import cv2
 import numpy as np
 import matplotlib.pyplot as plt
 
-from comparisons import histogram_comparison
+from comparisons import histogram_comparison, structural_similarity_index
 
 # Allows imports from the style transfer submodule
 sys.path.append('DCT-Net')
@@ -44,6 +44,7 @@ def compare_with_anime_characters(data: np.ndarray) -> int:
   data_rescaled = cv2.resize(data, example_face.shape[:2])
   plot_two_images(example_face, data_rescaled)
   print(histogram_comparison(data_rescaled, example_face))
+  print(f'structural-similarity: {structural_similarity_index(data_rescaled, example_face)}')
 
 
 def transfer_to_anime(img: np.ndarray):

requirements.txt

@@ -7,4 +7,5 @@ beautifulsoup4==4.11.1
 lxml==4.9.2
 opencv-python==4.7.0.68
 torch==1.13.1
-matplotlib==3.6.3
+matplotlib==3.6.3
+scikit-image==0.19.3